def test_remove_scan_op():
with pm.Model():
pm.Normal("n", 0, 1)
inference = ADVI()
buff = io.StringIO()
inference.run_profiling(n=10).summary(buff)
assert "aesara.scan.op.Scan" not in buff.getvalue()
buff.close()
def test_clear_cache():
import cloudpickle
with pm.Model():
pm.Normal("n", 0, 1)
inference = ADVI()
inference.fit(n=10)
assert any(len(c) != 0 for c in inference.approx._cache.values())
inference.approx._cache.clear()
# should not be cleared at this call
assert all(len(c) == 0 for c in inference.approx._cache.values())
new_a = cloudpickle.loads(cloudpickle.dumps(inference.approx))
assert not hasattr(new_a, "_cache")
inference_new = pm.KLqp(new_a)
inference_new.fit(n=10)
assert any(len(c) != 0 for c in inference_new.approx._cache.values())
inference_new.approx._cache.clear()
assert all(len(c) == 0 for c in inference_new.approx._cache.values())